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scVelo

By Theis laboratory / scVelo contributors →

RNA velocity and cellular dynamics analysis

RNA velocity and cellular dynamics analysis. Dynamical assumptions and data quality affect direction estimates; model choices include statistical and deep-learning methods.

RNA velocity and cellular dynamics analysisInput: Spliced and unspliced transcript measurementsOutput: Velocity estimates, latent time and kinetic parameters
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Overview

RNA velocity and cellular dynamics analysis. Dynamical assumptions and data quality affect direction estimates; model choices include statistical and deep-learning methods.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 16/09/2026, 17:33:40

Key Features

  • RNA velocity and cellular dynamics analysis
  • Input: Spliced and unspliced transcript measurements
  • Output: Velocity estimates, latent time and kinetic parameters

Academic Context & Research Evidence

Biological & Workflow Fit

Compute & Hardware
Consult linked installation guidance; workload dependent
Licensing & Academic Use
Review the linked release, model weights, datasets and service terms separately
Documented Evidence
Project or provider documentation; no local performance benchmark

Cite this Tool

Use this citation format when referencing scVelo in scientific publications and benchmark papers.

@software{scvelo_2026,
  title = {{scVelo}},
  author = {{Theis laboratory / scVelo contributors}},
  year = {2026},
  url = {https://github.com/theislab/scvelo},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for scVelo.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeResearch software / model
Access modePublic code / project terms
AI roleStatistical and model-dependent machine learning
Input dataSpliced and unspliced transcript measurements
Output dataVelocity estimates, latent time and kinetic parameters
Licence conditionsReview the linked release, model weights, datasets and service terms separately
Commercial eligibilityNot independently confirmed
Compute requirementsConsult linked installation guidance; workload dependent
ValidationEvaluate on representative data; no clinical suitability established
TypeNot recorded
Intended useBiological and pharmaceutical research
CompatibilityNot recorded
LimitationsDynamical assumptions and data quality affect direction estimates; model choices include statistical and deep-learning methods.
Evidence levelProject or provider documentation; no local performance benchmark
AvailabilitySee project access and maintenance status
Price / accessSee project terms; compute costs may apply

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for scVelo yet. Visit the official resource below for manufacturer imagery.

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FAQ

Where is this product available?

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating scVelo.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5